alexa Effects of squeeze casting parameters on solidification time based on neural network
Engineering

Engineering

Advances in Automobile Engineering

Author(s): Rong Ji Wang, Wen Fang Tan, DianWu Zhou

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Based on artificial neural network (ANN) and ProCast software, the effects of different process parameter on the solidification time of squeeze casting hot die steel were investigated, such as interfacial heat transfer coefficient of metal/cavity die (h1), applied pressure (Pa), interfacial heat transfer coefficient of metal/male die (h2), die pre-heat temperature (Td) and pouring temperature (Tp). An ANN model on the relationship between process parameters and solidification time was constructed. The test results show that the ANN model is reasonable and can accurately predict the solidification time and the influence of process parameters on solidification time. The most important parameter is Td, and the secondary is Tp. While Td and Tp increasing within a certain range, the solidification time is found to increase, in contrast, Pa causes the solidification time to decrease. However, h1 and h2 increasing within a certain range, the solidification time is found to decrease. Moreover, the solidification time increases rapidly when h1 and h2 are above their respective critical point. The critical value increases with an increase in mould thickness

This article was published in inderscience publishers and referenced in Advances in Automobile Engineering

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